Previous epidemiological studies have shown that the metabolic syndrome is very common with a population prevalence of ~30% in middle-aged Americans. The metabolic syndrome predisposes to coronary artery disease, the major cause of death in the U.S. Elevated plasma triglycerides (TGs) and low high-density lipoprotein cholesterol (HDL-C) are the key atherogenic lipid phenotypes ofthe metabolic syndrome. However, the genetic basis for the metabolic syndrome is not well understood. The major goal of project 2 is to systematically identify DNA sequence variants, genes and metabolic pathways contributing to the lipid traits, TGs and HDL-C, of the metabolic syndrome and to investigate the sequence variants for risk as well as for gene-gene and gene-environment interacfions in the populafion. Specific Aimi focuses on resequencing ofthe genes we identified during the previous cycle of this Project 2 (WWOX and LMFI) to identify the variants exhibiting the strongest phenotypic effects. These variants will be further investigated in functional studies. Our ultimate goal is to provide novel biomarkers and targets for clinical interventions. Specific Aim 2 integrates genomic data obtained from mouse and human to systemically identify novel genes and pathways implicated at the DNA and RNA level in the metabolic syndrome related lipid traits in human. As an individual's risk to develop a complex cardiovascular phenotype is a combination of suscepfibility variants, environmental factors, behavior and chance, we will investigate the DNA sequence variants supported by multiple lines of evidence for risk as well as for gene-gene and gene-environment interactions in a large populafion sample, the METabolic Syndrome In Men (METSIM) study, comprising currenfiy 8,600 Finns, and ultimately 10,000 Finns in 2010. This study will be performed in collaboration with Dr. Markku Laakso, University of Kuopio, Finland who is collecfing the METSIM sample. Ufilizing this extensive population sample with refined phenotypes available for the study gives us a unique opportunity to explore the population risks and gene-environment interactions. The gene-environment interactions, critical for the expression of complex traits, have not been investigated in the r;ecent genome-wide association studies, because there are very few large enough population samples such as the METSIM study with refined enough phenotypic informafion available for gene-environment interaction analyses. Elucidafion of the unknown genefic factors and molecular mechanisms influencing the high suscepfibility to the metabolic syndrome in human is of great relevance to the American healthcare system.